Blind zones, or blind spots, in a vehicle are a leading cause of accidents between vehicles. Studies show that a majority of drivers do not know how to align mirrors correctly. Furthermore, when drivers use vehicles that are not their own, or use a shared vehicle, drivers often find the process of manual mirror adjustment of vehicle mirrors to be too bothersome for a single trip.
Current blind-spot detection systems are expensive (since they typically use radar), and tend to warn the user about vehicles that are in certain pre-determined zones around the vehicle. The warning is provided regardless of whether the driver is actually able to see surrounding vehicles or not. A decision to alert the driver (or not) is based on an assumption about typical blind spots in the field of view (FOV) of the driver, but does not rely on knowledge of the actual blind-spots of each particular driver. Many vehicles are being equipped with in-car camera systems that monitor attentiveness and drowsiness of the driver.
It would be desirable to implement a blind-spot monitoring using machine vision and precise FOV information to determine blind spots and to warn drivers in order to significantly increase driver safety.